Amortized efficiency of list update and paging rules
Communications of the ACM
Stochastic on-line knapsack problems
Mathematical Programming: Series A and B
Optimal time-critical scheduling via resource augmentation (extended abstract)
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Average-case analysis of off-line and on-line knapsack problems
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Speed is as powerful as clairvoyance
Journal of the ACM (JACM)
Resource augmentation for online bounded space bin packing
Journal of Algorithms
Removable Online Knapsack Problems
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
An Online Partially Fractional Knapsack Problem
ISPAN '05 Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks
On the advice complexity of the knapsack problem
LATIN'12 Proceedings of the 10th Latin American international conference on Theoretical Informatics
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It is known that online knapsack is not competitive. This negative result remains true even if items are removable. In this paper we consider online removable knapsack with resource augmentation, in which we hold a knapsack of capacity R=1 and aim at maintaining a feasible packing to maximize the total profit of items packed into the knapsack. Both scenarios that removal of accepted items is allowed and is not allowed are investigated. We evaluate an online algorithm by comparing the resulting packing to an optimal packing that uses a knapsack of capacity one. Optimal online algorithms are derived for both the weighted case (items have arbitrary profits) and the unweighted case (the profit of an item is equal to its size).